The present invention relates to modeling the heart in medical images, and more particularly, to using personalized 4D anatomical heart model of the full cardiac system estimated from volumetric image sequences for decision support in diagnosis and treatment of cardiac disease.
Cardiac disease is the leading cause of death for men and women in the United States and accounts no less than 30% of deaths worldwide. Although medical advances in recent years have provided important improvements in the diagnosis and treatment of complex cardiac diseases such as valvular disease, thoracic aortic aneurysm, and Tetralogy of Fallot, the incidence of premature morbidity and mortality is still large. Medical imaging modalities, such as computed tomography (CT), magnetic resonance (MR), rotational X-ray, and Ultrasound, can be used to acquire large amounts of morphological and functional image data with a high temporal-spatial resolution. However, due to a lag in data understanding capabilities, physicians are forced to make vital decisions based on measurements and methods that are limited in scope. Thus, for many cardiac diseases, there is currently no prognostic model that allows comprehensive decision-making regarding optimal patient assessment, surgical intervention, or the extent of the cardiac disease. These limitations are at least in part due to the lack of efficient and accurate estimation of patient-specific parameters describing the heart-aortic anatomy, physiology, and hemodynamics, as well as the lack of disease progression models.